Propofol directly binds and inhibits skeletal muscle ryanodine receptor 1 (RyR1)
Bibliographic record
Abstract
Abstract As the primary Ca 2+ release channel in skeletal muscle sarcoplasmic reticulum (SR), mutations in the type 1 ryanodine receptor (RyR1) or its binding partners underlie a constellation of muscle disorders, including malignant hyperthermia (MH). In patients with MH mutations, exposure to triggering drugs such as the halogenated volatile anesthetics biases RyR1 to an open state, resulting in uncontrolled Ca 2+ release, sarcomere tension and heat production. Restoration of Ca 2+ into the SR also consumes ATP, generating a further untenable metabolic load. When anesthetizing patients with known MH mutations, the non-triggering intravenous general anesthetic propofol is commonly substituted for triggering anesthetics. Evidence of direct binding of anesthetic agents to RyR1 or its binding partners is scant, and the atomic-level interactions of propofol with RyR1 are entirely unknown. Here, we show that propofol decreases RyR1 opening in heavy SR vesicles and planar lipid bilayers, and that it inhibits activator-induced Ca 2+ release from SR in human skeletal muscle. In addition to confirming direct binding, photoaffinity labeling using m- azipropofol (AziP m ) revealed several putative propofol binding sites on RyR1. Prediction of binding affinity by molecular dynamics simulation suggests that propofol binds at least one of these sites at clinical concentrations. These findings invite the hypothesis that in addition to propofol not triggering MH, it may also be protective against MH by inhibiting induced Ca 2+ flux through RyR1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".